Enhancing real estate mass appraisal in Type II metropolitan cities: A GIS-MGWR approach
DOI: https://doi.org/10.3846/ijspm.2025.24225Abstract
At present, China’s real estate appraisal sector confronts a number of challenges, including low appraisal efficiency, significant human influence, lack of objectivity, and absence of unified standards. Particularly, conducting a scientific, precise, and efficient mass appraisal of existing housing is vital for fostering the industry‘s healthy development. This study adopts Zhangjiakou City in Hebei Province as a case study, integrating Geographic Information Systems (GIS) and utilizing the Ordinary Least Squares (OLS), Geographically Weighted Regression (GWR), Semi-parametric Geographically Weighted Regression (SGWR), and Multiscale Geographically Weighted Regression (MGWR) models to assess the prices of existing housing. The research delves into the specific challenges in mass appraisal of real estate within Type II metropolitan cities. The study reveals spatial heterogeneity in the prices of existing housing in Zhangjiakou City and shows that the MGWR model excels in mass appraisal of housing prices in Type II metropolitan cities. This research offers strategic guidance for real estate market investment and transactions in Zhangjiakou City and provides valuable references for other Type II metropolitan cities in real estate appraisal practices, market analysis, and policy formulation.
Keywords:
housing price, mass appraisal, real estate, Geographic Information Systems (GIS), Multiscale Geographically Weighted Regression (MGWR), spatial autocorrelation, Type II metropolitan citiesHow to Cite
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Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University.
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Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University.
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